EXONEST: BAYESIAN MODEL SELECTION APPLIED TO THE DETECTION AND CHARACTERIZATION OF EXOPLANETS VIA PHOTOMETRIC VARIATIONS
EXONEST: BAYESIAN MODEL SELECTION APPLIED TO THE DETECTION AND CHARACTERIZATION OF EXOPLANETS VIA PHOTOMETRIC VARIATIONS
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EXONEST：贝叶斯模型选择应用于通过光度变化检测和表征系外行星
DOI：
10.1088/0004-637x/795/2/112
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发表时间：
2013
期刊：
影响因子：
--
通讯作者：
D. Angerhausen
中科院分区：
文献类型：
--
作者：
Ben Placek;K. Knuth;D. Angerhausen
EXONEST是一种专门用于探测和表征系外行星光度学特征的算法，这些特征包括反射和热发射、多普勒增强和椭球变化。使用贝叶斯推理，我们可以在描述数据的竞争模型之间进行测试，并估计模型参数。我们通过测试圆形和偏心行星轨道模型，以及测试四种光度效应的存在或不存在来演示这种方法。除了使用贝叶斯模型选择，EXONEST的一个独特方面是潜在的区分对光曲线的反射和热贡献的能力。利用凌日行星KOI-13b上记录的开普勒数据，给出了一个实例研究。通过只考虑光曲线的非跃迁部分，我们证明了估计KOI-13b的光度相关模型参数是可能的。此外，贝叶斯模型测试证实，KOI-13b的轨道具有可检测的偏心。
EXONEST is an algorithm dedicated to detecting and characterizing the photometric signatures of exoplanets, which include reflection and thermal emission, Doppler boosting, and ellipsoidal variations. Using Bayesian inference, we can test between competing models that describe the data as well as estimate model parameters. We demonstrate this approach by testing circular versus eccentric planetary orbital models, as well as testing for the presence or absence of four photometric effects. In addition to using Bayesian model selection, a unique aspect of EXONEST is the potential capability to distinguish between reflective and thermal contributions to the light curve. A case study is presented using Kepler data recorded from the transiting planet KOI-13b. By considering only the nontransiting portions of the light curve, we demonstrate that it is possible to estimate the photometrically relevant model parameters of KOI-13b. Furthermore, Bayesian model testing confirms that the orbit of KOI-13b has a detectable eccentricity.
影响因子：
4.9
作者：
Borucki, William J.;Koch, David G.;Still, Martin
通讯作者：
Still, Martin